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   "cells": [
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     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Fitting data\n",
      "======================================================================\n",
      "\n",
      "This page shows you how to fit experimental data and plots the results\n",
      "using matplotlib.\n",
      "\n",
      "<TableOfContents>\n",
      "\n",
      "Fit examples with sinusoidal functions\n",
      "--------------------------------------\n",
      "\n",
      "### Generating the data\n",
      "\n",
      "Using real data is much more fun, but, just so that you can reproduce\n",
      "this example I will generate data to fit"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "from numpy import pi, r_\n",
      "import matplotlib.pyplot as plt\n",
      "from scipy import optimize\n",
      "\n",
      "# Generate data points with noise\n",
      "num_points = 150\n",
      "Tx = np.linspace(5., 8., num_points)\n",
      "Ty = Tx\n",
      "\n",
      "tX = 11.86*np.cos(2*pi/0.81*Tx-1.32) + 0.64*Tx+4*((0.5-np.random.rand(num_points))*np.exp(2*np.random.rand(num_points)**2))\n",
      "tY = -32.14*np.cos(2*np.pi/0.8*Ty-1.94) + 0.15*Ty+7*((0.5-np.random.rand(num_points))*np.exp(2*np.random.rand(num_points)**2))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Fitting the data\n",
      "\n",
      "We now have two sets of data: Tx and Ty, the time series, and tX and tY,\n",
      "sinusoidal data with noise. We are interested in finding the frequency\n",
      "of the sine wave."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Fit the first set\n",
      "fitfunc = lambda p, x: p[0]*np.cos(2*np.pi/p[1]*x+p[2]) + p[3]*x # Target function\n",
      "errfunc = lambda p, x, y: fitfunc(p, x) - y # Distance to the target function\n",
      "p0 = [-15., 0.8, 0., -1.] # Initial guess for the parameters\n",
      "p1, success = optimize.leastsq(errfunc, p0[:], args=(Tx, tX))\n",
      "\n",
      "time = np.linspace(Tx.min(), Tx.max(), 100)\n",
      "plt.plot(Tx, tX, \"ro\", time, fitfunc(p1, time), \"r-\") # Plot of the data and the fit\n",
      "\n",
      "# Fit the second set\n",
      "p0 = [-15., 0.8, 0., -1.]\n",
      "p2,success = optimize.leastsq(errfunc, p0[:], args=(Ty, tY))\n",
      "\n",
      "time = np.linspace(Ty.min(), Ty.max(), 100)\n",
      "plt.plot(Ty, tY, \"b^\", time, fitfunc(p2, time), \"b-\")\n",
      "\n",
      "# Legend the plot\n",
      "plt.title(\"Oscillations in the compressed trap\")\n",
      "plt.xlabel(\"time [ms]\")\n",
      "plt.ylabel(\"displacement [um]\")\n",
      "plt.legend(('x position', 'x fit', 'y position', 'y fit'))\n",
      "\n",
      "ax = plt.axes()\n",
      "\n",
      "plt.text(0.8, 0.07,\n",
      "         'x freq :  %.3f kHz \\n y freq :  %.3f kHz' % (1/p1[1],1/p2[1]),\n",
      "         fontsize=16,\n",
      "         horizontalalignment='center',\n",
      "         verticalalignment='center',\n",
      "         transform=ax.transAxes)\n",
      "\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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KQG/1zTdw663OuXXZWilr6mXTtSv88AM0b+7WImuyNj2d1SNGMC0nB4DJVq4L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\nAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fab9d972190>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### A clever use of the cost function\n",
      "\n",
      "Suppose that you have the same data set: two time-series of oscillating\n",
      "phenomena, but that you know that the frequency of the two oscillations\n",
      "is the same. A clever use of the cost function can allow you to fit both\n",
      "set of data in one fit, using the same frequency. The idea is that you\n",
      "return, as a \"cost\" array, the concatenation of the costs of your two\n",
      "data sets for one choice of parameters. Thus the leastsq routine is\n",
      "optimizing both data sets at the same time."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Target function\n",
      "fitfunc = lambda T, p, x: p[0]*np.cos(2*np.pi/T*x+p[1]) + p[2]*x\n",
      "# Initial guess for the first set's parameters\n",
      "p1 = r_[-15., 0., -1.]\n",
      "# Initial guess for the second set's parameters\n",
      "p2 = r_[-15., 0., -1.]\n",
      "# Initial guess for the common period\n",
      "T = 0.8\n",
      "# Vector of the parameters to fit, it contains all the parameters of the problem, and the period of the oscillation is not there twice !\n",
      "p = r_[T, p1, p2]\n",
      "# Cost function of the fit, compare it to the previous example.\n",
      "errfunc = lambda p, x1, y1, x2, y2: r_[\n",
      "                fitfunc(p[0], p[1:4], x1) - y1,\n",
      "                fitfunc(p[0], p[4:7], x2) - y2\n",
      "            ]\n",
      "# This time we need to pass the two sets of data, there are thus four \"args\".\n",
      "p,success = optimize.leastsq(errfunc, p, args=(Tx, tX, Ty, tY))\n",
      "time = np.linspace(Tx.min(), Tx.max(), 100) # Plot of the first data and the fit\n",
      "plt.plot(Tx, tX, \"ro\", time, fitfunc(p[0], p[1:4], time),\"r-\")\n",
      "\n",
      "# Plot of the second data and the fit\n",
      "time = np.linspace(Ty.min(), Ty.max(),100)\n",
      "plt.plot(Ty, tY, \"b^\", time, fitfunc(p[0], p[4:7], time),\"b-\")\n",
      "\n",
      "# Legend the plot\n",
      "plt.title(\"Oscillations in the compressed trap\")\n",
      "plt.xlabel(\"time [ms]\")\n",
      "plt.ylabel(\"displacement [um]\")\n",
      "plt.legend(('x position', 'x fit', 'y position', 'y fit'))\n",
      "\n",
      "ax = plt.axes()\n",
      "\n",
      "plt.text(0.8, 0.07,\n",
      "         'x freq :  %.3f kHz' % (1/p[0]),\n",
      "         fontsize=16,\n",
      "         horizontalalignment='center',\n",
      "         verticalalignment='center',\n",
      "         transform=ax.transAxes)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "<matplotlib.text.Text at 0x7fab996e5b90>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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JFs7zzcpyfWEAZGcDO3aIcx+AqZ39nXdGoXv3eLsmpdR2H8rMLIOtW/uBdHxF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\n2ecAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fab9d865690>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Simplifying the syntax\n",
      "----------------------\n",
      "\n",
      "Especially when using fits for interactive use, the standard syntax for\n",
      "optimize.leastsq can get really long. Using the following script can\n",
      "simplify your life:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "from scipy import optimize\n",
      "\n",
      "class Parameter:\n",
      "    def __init__(self, value):\n",
      "            self.value = value\n",
      "\n",
      "    def set(self, value):\n",
      "            self.value = value\n",
      "\n",
      "    def __call__(self):\n",
      "            return self.value\n",
      "\n",
      "def fit(function, parameters, y, x = None):\n",
      "    def f(params):\n",
      "        i = 0\n",
      "        for p in parameters:\n",
      "            p.set(params[i])\n",
      "            i += 1\n",
      "        return y - function(x)\n",
      "\n",
      "    if x is None: x = np.arange(y.shape[0])\n",
      "    p = [param() for param in parameters]\n",
      "    return optimize.leastsq(f, p)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now fitting becomes really easy, for example fitting to a gaussian:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# giving initial parameters\n",
      "mu = Parameter(7)                     \n",
      "sigma = Parameter(3)\n",
      "height = Parameter(5)\n",
      "\n",
      "# define your function:\n",
      "def f(x): return height() * np.exp(-((x-mu())/sigma())**2) \n",
      "\n",
      "# fit! (given that data is an array with the data to fit)\n",
      "data = 10*np.exp(-np.linspace(0, 10, 100)**2) + np.random.rand(100)\n",
      "print fit(f, [mu, sigma, height], data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(array([ -1.7202343 ,  12.29906459,  10.74194291]), 1)\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Fitting gaussian-shaped data\n",
      "----------------------------\n",
      "\n",
      "### Calculating the moments of the distribution\n",
      "\n",
      "Fitting gaussian-shaped data does not require an optimization routine.\n",
      "Just calculating the moments of the distribution is enough, and this is\n",
      "much faster.\n",
      "\n",
      "However this works only if the gaussian is not cut out too much, and if\n",
      "it is not too small."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gaussian = lambda x: 3*np.exp(-(30-x)**2/20.)\n",
      "\n",
      "data = gaussian(np.arange(100))\n",
      "\n",
      "plt.plot(data, '.')\n",
      "\n",
      "X = np.arange(data.size)\n",
      "x = np.sum(X*data)/np.sum(data)\n",
      "width = np.sqrt(np.abs(np.sum((X-x)**2*data)/np.sum(data)))\n",
      "\n",
      "max = data.max()\n",
      "\n",
      "fit = lambda t : max*np.exp(-(t-x)**2/(2*width**2))\n",
      "\n",
      "plt.plot(fit(X), '-')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "[<matplotlib.lines.Line2D at 0x7fab9977d990>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7fab9977d390>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Fitting a 2D gaussian\n",
      "\n",
      "Here is robust code to fit a 2D gaussian. It calculates the moments of\n",
      "the data to guess the initial parameters for an optimization routine.\n",
      "For a more complete gaussian, one with an optional additive constant and\n",
      "rotation, see\n",
      "<http://code.google.com/p/agpy/source/browse/trunk/agpy/gaussfitter.py>.\n",
      "It also allows the specification of a known error."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def gaussian(height, center_x, center_y, width_x, width_y):\n",
      "    \"\"\"Returns a gaussian function with the given parameters\"\"\"\n",
      "    width_x = float(width_x)\n",
      "    width_y = float(width_y)\n",
      "    return lambda x,y: height*np.exp(\n",
      "                -(((center_x-x)/width_x)**2+((center_y-y)/width_y)**2)/2)\n",
      "\n",
      "def moments(data):\n",
      "    \"\"\"Returns (height, x, y, width_x, width_y)\n",
      "    the gaussian parameters of a 2D distribution by calculating its\n",
      "    moments \"\"\"\n",
      "    total = data.sum()\n",
      "    X, Y = np.indices(data.shape)\n",
      "    x = (X*data).sum()/total\n",
      "    y = (Y*data).sum()/total\n",
      "    col = data[:, int(y)]\n",
      "    width_x = np.sqrt(np.abs((np.arange(col.size)-x)**2*col).sum()/col.sum())\n",
      "    row = data[int(x), :]\n",
      "    width_y = np.sqrt(np.abs((np.arange(row.size)-y)**2*row).sum()/row.sum())\n",
      "    height = data.max()\n",
      "    return height, x, y, width_x, width_y\n",
      "\n",
      "def fitgaussian(data):\n",
      "    \"\"\"Returns (height, x, y, width_x, width_y)\n",
      "    the gaussian parameters of a 2D distribution found by a fit\"\"\"\n",
      "    params = moments(data)\n",
      "    errorfunction = lambda p: np.ravel(gaussian(*p)(*np.indices(data.shape)) -\n",
      "                                 data)\n",
      "    p, success = optimize.leastsq(errorfunction, params)\n",
      "    return p"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And here is an example using it:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Create the gaussian data\n",
      "Xin, Yin = np.mgrid[0:201, 0:201]\n",
      "data = gaussian(3, 100, 100, 20, 40)(Xin, Yin) + np.random.random(Xin.shape)\n",
      "\n",
      "plt.matshow(data, cmap=plt.cm.gist_earth_r)\n",
      "\n",
      "params = fitgaussian(data)\n",
      "fit = gaussian(*params)\n",
      "\n",
      "plt.contour(fit(*np.indices(data.shape)), cmap=plt.cm.copper)\n",
      "ax = plt.gca()\n",
      "(height, x, y, width_x, width_y) = params\n",
      "\n",
      "plt.text(0.95, 0.05, \"\"\"\n",
      "x : %.1f\n",
      "y : %.1f\n",
      "width_x : %.1f\n",
      "width_y : %.1f\"\"\" %(x, y, width_x, width_y),\n",
      "        fontsize=16, horizontalalignment='right',\n",
      "        verticalalignment='bottom', transform=ax.transAxes)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "<matplotlib.text.Text at 0x7fab9d8a4dd0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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injrNkv1pjIZOZPky8tkkFZ07URmrEEkV+JeHkcm01DbcgFyqxTH3HJ0H3s3543+LMC8h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\n3kbVhr3o6jrwTp2n6bq7GH/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kceO1tfWUpOSzMeoMfZSKWYZv+yIioRSZxsjqyku0DdyJ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sURzZwsh7WLkdhoZfY+TgFjvXZ6iMvIZudEkSk3+9IvPBAzLHKiHVoyqq5lA5kLDzagGvqbH2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chSV6HOKkCeUpOeVkK6sRqfbQwf07gne0mlEhgaVzLZ8RVG3QKyVFXYrF1CQxZxGhbbSYxl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3yEhcnn\nkRXU1PfeyviJx/GmxtBK61BLK1FKjESLDro3fpiIZxGtvpbZlWfpv+UzsJqgmC3g9l/h2vQKb55Z\n5uSpE1wamWDVG/yLE8OfUyg8AFwCfMADgBz4KfAhIPX2MX8YSwJPvsN5hoH+v+TDlZSU/FWcAvb8\nJW/4U4nhPuDfWCsuilkrQtYAo0Av8C9vH/eVP4r9uateS0pKSkpKSkpKSkpKSkpKSkpKSkpKSkpK\nSkpKSkpKSkpKSkpKSkpKSv58/w+5BqRmcihWdAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fab9d87ff50>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Fitting a power-law to data with errors\n",
      "---------------------------------------\n",
      "\n",
      "### Generating the data\n",
      "\n",
      "Generate some data with noise to demonstrate the fitting procedure. Data\n",
      "is generated with an amplitude of 10 and a power-law index of -2.0.\n",
      "Notice that all of our data is well-behaved when the log is taken... you\n",
      "may have to be more careful of this for real data."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Define function for calculating a power law\n",
      "powerlaw = lambda x, amp, index: amp * (x**index)\n",
      "\n",
      "##########\n",
      "# Generate data points with noise\n",
      "##########\n",
      "num_points = 20\n",
      "\n",
      "# Note: all positive, non-zero data\n",
      "xdata = np.linspace(1.1, 10.1, num_points) \n",
      "ydata = powerlaw(xdata, 10.0, -2.0)     # simulated perfect data\n",
      "yerr = 0.2 * ydata                      # simulated errors (10%)\n",
      "\n",
      "ydata += np.random.randn(num_points) * yerr       # simulated noisy data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Fitting the data\n",
      "\n",
      "If your data is well-behaved, you can fit a power-law function by first\n",
      "converting to a linear equation by using the logarithm. Then use the\n",
      "optimize function to fit a straight line. Notice that we are weighting\n",
      "by positional uncertainties during the fit. Also, the best-fit\n",
      "parameters uncertainties are estimated from the variance-covariance\n",
      "matrix. You should read up on when it may not be appropriate to use this\n",
      "form of error estimation. If you are trying to fit a power-law\n",
      "distribution, [this\n",
      "solution](http://code.google.com/p/agpy/wiki/PowerLaw?ts=1251337886&updated=PowerLaw)\n",
      "is more appropriate."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "##########\n",
      "# Fitting the data -- Least Squares Method\n",
      "##########\n",
      "\n",
      "# Power-law fitting is best done by first converting\n",
      "# to a linear equation and then fitting to a straight line.\n",
      "# Note that the `logyerr` term here is ignoring a constant prefactor.\n",
      "#\n",
      "#  y = a * x^b\n",
      "#  log(y) = log(a) + b*log(x)\n",
      "#\n",
      "\n",
      "logx = np.log10(xdata)\n",
      "logy = np.log10(ydata)\n",
      "logyerr = yerr / ydata\n",
      "\n",
      "# define our (line) fitting function\n",
      "fitfunc = lambda p, x: p[0] + p[1] * x   \n",
      "errfunc = lambda p, x, y, err: (y - fitfunc(p, x)) / err\n",
      "\n",
      "pinit = [1.0, -1.0]\n",
      "out = optimize.leastsq(errfunc, pinit,\n",
      "                       args=(logx, logy, logyerr), full_output=1)\n",
      "\n",
      "pfinal = out[0]\n",
      "covar = out[1]\n",
      "print pfinal\n",
      "print covar\n",
      "\n",
      "index = pfinal[1]\n",
      "amp = 10.0**pfinal[0]\n",
      "\n",
      "indexErr = np.sqrt( covar[1][1] ) \n",
      "ampErr = np.sqrt( covar[0][0] ) * amp\n",
      "\n",
      "##########\n",
      "# Plotting data\n",
      "##########\n",
      "\n",
      "plt.clf()\n",
      "plt.subplot(2, 1, 1)\n",
      "plt.plot(xdata, powerlaw(xdata, amp, index))     # Fit\n",
      "plt.errorbar(xdata, ydata, yerr=yerr, fmt='k.')  # Data\n",
      "plt.text(5, 6.5, 'Ampli = %5.2f +/- %5.2f' % (amp, ampErr))\n",
      "plt.text(5, 5.5, 'Index = %5.2f +/- %5.2f' % (index, indexErr))\n",
      "plt.title('Best Fit Power Law')\n",
      "plt.xlabel('X')\n",
      "plt.ylabel('Y')\n",
      "plt.xlim(1, 11)\n",
      "\n",
      "plt.subplot(2, 1, 2)\n",
      "plt.loglog(xdata, powerlaw(xdata, amp, index))\n",
      "plt.errorbar(xdata, ydata, yerr=yerr, fmt='k.')  # Data\n",
      "plt.xlabel('X (log scale)')\n",
      "plt.ylabel('Y (log scale)')\n",
      "plt.xlim(1.0, 11)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[ 1.00341313 -2.00447676]\n",
        "[[ 0.01592265 -0.0204523 ]\n",
        " [-0.0204523   0.03027352]]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "(1.0, 11)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7fab9d8dbd50>"
       ]
      }
     ],
     "prompt_number": 10
    }
   ],
   "metadata": {}
  }
 ]
}
